Teaching form
Blended learning: Face-to-face lectures and practical sessions with online learning modules, and group work.
First Lecture: April 18th 2024, at LE/LE105
Working Language
English
Description
Computers and 'machine-intelligence' are frequently discussed as the means for addressing today's critical educational challenges: learning remotely, learning at one's own pace, learning according to one's needs and background, providing quality education to all and for all. In this course, we welcome all master-level students with technical or non-technical backgrounds. Through the semester, we will cover topics on the intersection of Artificial Intelligence in Education, Educational Technologies, and Human-Computer Interaction and we will carry out hands-on exercises to deepen our understanding of intelligent learning technologies. Specifically, we will go over the following:
- Introduction to educational technologies
- Artificial intelligence in education (AIED)
- Student Modeling
- Intelligent Tutoring Systems (ITS)
- Collaborative learning environments / MOOCs
- Learning Management Systems / Open Educational Resources
- Fairness, Accountability, Transparency, and Ethics in AIED.
Learning Objectives
Students will learn about the state-of-the-art research in Educational Technologies with a focus on Artificial Intelligence in Education. They will familiarize themselves with algorithmic techniques for modeling cognition and knowledge, and they will explore how these representations are used in practice. Students will explore various learning environments supported by "intelligent" algorithms and will learn about using technology as a tool and means for orchestrating learning.
Literature
- How People Learn: Brain, Mind, Experience, and School: Expanded Edition (2000), National Research Council.
- Handbook of design in educational technology, edited by Rosemary Luckin, Sadhana Puntambekar, Peter Goodyear, Barbara Grabowski, Joshua Underwood, and Niall Winters.
- selected publications (research/news articles)
Pre-qualifications
None
Registration
All prospective students are requested to self-enroll in the Moodle module of the course (https://moodle.uni-due.de/user/index.php?id=44394)
For questions, please contact Prof. Dr. Irene-Angelica Chounta |
